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Title: Quantification of slope deformation behaviour using acoustic emission monitoring
Author: Smith, Alister
ISNI:       0000 0004 5357 4630
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2015
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Early warning of slope instability will enable evacuation of vulnerable people and timely repair and maintenance of critical infrastructure. However, currently available warning systems are too expensive for wide-scale use or have technical limitations. The acoustic emission (AE) monitoring approach using active waveguides (i.e. a steel tube with granular backfill surround installed in a borehole through a slope), in conjunction with the Slope ALARMS AE measurement system, has the potential to be an affordable early warning system for slope instability. However, the challenge has been to develop strategies to interpret and quantify deformation behaviour from measured AE. The development of an approach to quantify slope deformation behaviour from measured AE will enable the AE monitoring system to provide early warning of slope instability through detecting, quantifying and communicating accelerations in slope movement. Field monitoring and full-scale physical modelling have been conducted to characterise the AE response from the system to both reactivated slope movements and first-time slope failure. Definitive field evidence has been obtained showing AE monitoring can measure slope movements and generated AE rates are proportional to slope displacement rates, which was confirmed through comparisons with both conventional inclinometer and continuous ShapeAccelArray deformation measurements. A field monitoring case study demonstrated that the AE approach can detect very slow slope movements of 0.075 mm/day. In addition, the concept of retrofitting inclinometer casings with active waveguides to convert the manually read instrument to a real-time monitoring system has been demonstrated using a field trial. Dynamic strain-controlled shear tests on active waveguide physical models demonstrated that AE monitoring can be used to quantify slope displacement rates, continuously and in real-time, with accuracy to within an order of magnitude. Large-scale first-time slope failure experiments allowed the AE response to slope failure to be characterised. AE was detected after shear deformations of less than a millimetre in previously un-sheared material, and AE rates increased proportionally with displacement rates as failure occurred. The AE rate-displacement rate relationship can be approximated as linear up to 100 mm/hour and shear surface deformations less than 10-20 mm. At greater velocities and larger deformations the gradient of the relationship progressively increases and is best represented using a polynomial. This is because complex pressure distributions develop along the active waveguide analogous to a laterally loaded pile, and the confining pressures increase. Variables that influence the AE rate-displacement rate relationship have been quantified using physical model experiments and empirical relationships. A framework has been developed to allow AE rate-displacement rate calibration relationships to be determined for any AE system installation. This provides a universal method that can be used by practitioners when installing AE systems, to calibrate them to deliver alarm statuses/warning levels that are related to slope displacement rates. Use of this framework has been demonstrated using a case study example, and decision making protocols have been suggested that use trends in alarms with time to trigger decisions, which could be to send an engineer to inspect the slope, manage traffic, or evacuate people.
Supervisor: Not available Sponsor: Engineering and Physical Sciences Research Council ; Loughborough University
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Acoustic Emission (AE) ; Geotechnical engineering ; Slopes ; Landslides ; Field monitoring ; Physical modelling ; Deformation ; Instrumentation ; Early warning